data: mean [ OLE2 CPT ESCENARIO2 PROBABILIDADESWETDAYS ]

served from 129.236.110.25

mean [ OLE2 CPT ESCENARIO2 PROBABILIDADESWETDAYS ]: Probabilidades -Días Lluviosos data

mean [ OLE2 CPT ESCENARIO2 PROBABILIDADESWETDAYS ].

Independent Variables (Grids)

Forecast Lead Time in Months: grid: /L (months) ordered [ (2.5)] :grid
Hecho en (forecast_reference_time): grid: /S (months since 1960-01-01) ordered (0000 1 Jan 2000) to (0000 1 Mar 2025) by 1.0 N= 303 pts :grid
Longitude (longitude): grid: /X (degree_east) ordered (117.5W) to (28.5W) by 0.5 N= 179 pts :grid

Other Info

CE

null

colorscalename

halfgreyscale

CS

null

datatype

realarraytype

file_missing_value

fnname

maskle

maxncolor

254

missing_value

NaN

pointwidth

units

ids

history

[ dominant_class ( OLE2 CPT ESCENARIO2 WETDAY Sobre la Normal ) + masklt ( { [ dominant_class ( OLE2 CPT ESCENARIO2 WETDAY ) - 1. ] * 11. } , 22 ) ] + [ dominant_class ( OLE2 CPT ESCENARIO2 WETDAY Normal ) + masknotrange ( { [ dominant_class ( OLE2 CPT ESCENARIO2 WETDAY ) - 1. ] * 11. } , 10 , 12 ) ]

dominant_class [ OLE2 CPT ESCENARIO2 WETDAY Sobre la Normal ] + masklt [ ( { dominant_class [ OLE2 CPT ESCENARIO2 WETDAY ] - 1. } * 11. ) , 22 ]

dominant_class [ OLE2 CPT ESCENARIO2 WETDAY Sobre la Normal ]
dominant_class over WETDAY[<35, >80]

masklt [ ( { dominant_class [ OLE2 CPT ESCENARIO2 WETDAY ] - 1. } * 11. ) , 22 ]
dominant_class over C[Bajo la Normal, Sobre la Normal]

dominant_class [ OLE2 CPT ESCENARIO2 WETDAY Normal ] + masknotrange [ ( { dominant_class [ OLE2 CPT ESCENARIO2 WETDAY ] - 1. } * 11. ) , 10 , 12 ]

dominant_class [ OLE2 CPT ESCENARIO2 WETDAY Normal ]
dominant_class over WETDAY[<35, >80]

masknotrange [ ( { dominant_class [ OLE2 CPT ESCENARIO2 WETDAY ] - 1. } * 11. ) , 10 , 12 ]
dominant_class over C[Bajo la Normal, Sobre la Normal]

dominant_class [ OLE2 CPT ESCENARIO2 WETDAY Bajo la Normal ] + maskgt [ ( { dominant_class [ OLE2 CPT ESCENARIO2 WETDAY ] - 1. } * 11. ) , 0 ]

dominant_class [ OLE2 CPT ESCENARIO2 WETDAY Bajo la Normal ]
dominant_class over WETDAY[<35, >80]

maskgt [ ( { dominant_class [ OLE2 CPT ESCENARIO2 WETDAY ] - 1. } * 11. ) , 0 ]
dominant_class over C[Bajo la Normal, Sobre la Normal]

mean [ OLE2 CPT ESCENARIO2 PROBABILIDADESWETDAYS ]

Averaged over Y[63S, 33N] minimum 0.0% data present

Last updated: Thu, 06 Mar 2025 07:30:01 GMT
Expires: Sat, 05 Apr 2025 00:00:00 GMT

Data Views

	C	L	S	X	Y
OLE2 CPT ESCENARIO2[ABOVETMAX PROBABILIDADESWETDAYS BELOW SPEARMAN AFCTMIN TMIN BELOWTMED BELOWTMAX SPEARMANTMAX PRECIPITACION SPEARMANWET AFC PROPENSIONTMAX AFCTMED ODDSTMED WETDAY PROBABILIDADESTMIN ABOVEWET AFCTMAX PROPENSIONWETDAYS target_date AFCWET TMAX PROBABILIDADESTMAX SPEARMANTMIN ODDSWETDAYS ODDS PROPENSIONTMED BELOWWET ABOVETMIN ABOVE BELOWTMIN SPEARMANTMED ODDSTMAX ODDSTMIN PROPENSIONTMIN ABOVETMED PROBABILIDADES PROPENSION PROBABILIDADESTMED TMED ]
OLE2 CPT ESCENARIO2 ODDSTMED 2.5 months[ X Y C \| S L]	M	M	M	O=0.25	M
mean [ OLE2 CPT ESCENARIO2 PROBABILIDADESWETDAYS ] 2.5 months[ X \| L S]		M	M	M

Filters

Here are some filters that are useful for manipulating data. There are actually many more available, but they have to be entered manually. See Ingrid Function Documentation for more information.

Monthly Climatology calculates a monthly climatology by averaging over all years.
anomalies calculates the difference between the (above) monthly climatology and the original data.
Integrate along X S
Differentiate along X S
Take differences along X S

Average over X S | X S |
RMS (root mean square with mean *not* removed) over X S | X S |
RMSA (root mean square with mean removed) over X S | X S |
Maximum over X S | X S |
Minimum over X S | X S |
Detrend (best-fit-line) over X S | X S |

Note on units